| Frame | Time | Anger | Contempt | Disgust | Fear | Joy | Sad | Surprise | Neutral | ID |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.0000 | 0.0101 | 0.0218 | 0.0043 | 0.0541 | 0.5260 | 0.0959 | 0.0010 | 0.2868 | T001-001 |
| 1 | 0.0333 | 0.0101 | 0.0218 | 0.0043 | 0.0541 | 0.5260 | 0.0959 | 0.0010 | 0.2868 | T001-001 |
| 2 | 0.0667 | 0.0101 | 0.0218 | 0.0043 | 0.0541 | 0.5260 | 0.0959 | 0.0010 | 0.2868 | T001-001 |
| 3 | 0.1000 | 0.0080 | 0.0187 | 0.0032 | 0.0375 | 0.5353 | 0.1050 | 0.0011 | 0.2911 | T001-001 |
| 4 | 0.1333 | 0.0091 | 0.0380 | 0.0158 | 0.0036 | 0.6902 | 0.0177 | 0.0004 | 0.2252 | T001-001 |
| 5 | 0.1667 | 0.0104 | 0.0450 | 0.0139 | 0.0030 | 0.7157 | 0.0162 | 0.0003 | 0.1955 | T001-001 |
| Start | End | Event.Switch | Event.Type | Event | ID |
|---|---|---|---|---|---|
| 86.5 | 246.50 | 1 | 1 | Analytical Questions | T001-005 |
| 508.5 | 657.50 | 1 | 2 | Mathematical Questions | T001-005 |
| 107.5 | 269.25 | 1 | 3 | Emotional Questions | T001-006 |
| 521.0 | 674.75 | 1 | 3 | Emotional Questions | T001-006 |
| 81.0 | 240.00 | 1 | 4 | Texting | T001-007 |
| 510.0 | 671.00 | 1 | 4 | Texting | T001-007 |
Sample of Cleaned Data Showing an Event Transition
| Subject | Trial | Age | Gender | Frame | Time | Event.Switch | Event | Action | Anger | Contempt | Disgust | Fear | Joy | Sad | Surprise | Neutral | Texting |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| T001 | 007 | Y | M | 2427 | 80.900 | 0 | No Event | 0 | 0.0909 | 0.0575 | 0.4205 | 3e-04 | 0.0011 | 0.1343 | 0 | 0.2954 | 0 |
| T001 | 007 | Y | M | 2428 | 80.933 | 0 | No Event | 0 | 0.0612 | 0.0397 | 0.4293 | 4e-04 | 0.0011 | 0.1630 | 0 | 0.3052 | 0 |
| T001 | 007 | Y | M | 2429 | 80.967 | 0 | No Event | 0 | 0.1034 | 0.0963 | 0.3186 | 2e-04 | 0.0013 | 0.0856 | 0 | 0.3946 | 0 |
| T001 | 007 | Y | M | 2430 | 81.000 | 1 | Texting | 4 | 0.0363 | 0.4976 | 0.0171 | 1e-04 | 0.0024 | 0.0069 | 0 | 0.4396 | 1 |
| T001 | 007 | Y | M | 2431 | 81.033 | 1 | Texting | 4 | 0.0059 | 0.7285 | 0.0027 | 4e-04 | 0.0068 | 0.0063 | 0 | 0.2493 | 1 |
| T001 | 007 | Y | M | 2432 | 81.067 | 1 | Texting | 4 | 0.0058 | 0.6890 | 0.0035 | 4e-04 | 0.0077 | 0.0068 | 0 | 0.2868 | 1 |
Reproducible Research
Takeaways
Differences in variation between the trials suggest that it may be possible to build a model capable of predicting a texting event
Subject specific plots are unique enough that a individual subjects variables may be needed in modeling
Baseline Trial: Trial 4 was used as a baseline trial because the conditions were identical to the Texting Trial (dense traffic with detour)
Model Proposal:
Feed-Forward Neural Networks
Neural Network Components
Step 1: Initialize Model Weights are Random
Step 2: Calculate Hidden Weights and Output Node Prediction
Step 3: Update Weights Based on Error
Step 4: Repeat Steps 2-3 to update the hidden and output node values